69 lines
3.1 KiB
Markdown
69 lines
3.1 KiB
Markdown
# OSINT Person Intelligence MCP Pattern
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Build a dedicated entity-resolution layer above generic search MCPs when the task is person/skip-trace intelligence rather than raw search.
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## Architecture
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```
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Hermes
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↓
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osint-person-mcp # entity resolution, scoring, dossier logic
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↓
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super-search MCP # raw search + extraction providers
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↓
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SearXNG / Exa / OpenCorporates / CourtListener / Firecrawl
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```
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Keep `super-search` generic. Put identity-specific logic in a separate MCP so the generic search engine does not become a grab bag of scoring and compliance behavior.
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## Tool set
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Recommended tools:
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| Tool | Purpose |
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| `person_search` | Query generation, search, source scoring, entity clustering, compliance notes |
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| `phone_search_variants` | Normalize phone and emit common variants |
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| `phone_search` | Search all phone variants and cluster matches |
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| `email_search` | Search email address and cluster matches |
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| `business_affiliation_search` | Search person + organization/business/location anchors |
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| `court_business_search` | Search court/business/public-record query variants |
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| `score_source` | Score URL/title/description reliability |
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| `dossier_report` | Convert structured JSON into concise markdown report |
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## Source scoring
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Use durable source tiers:
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| Tier | Examples | Treatment |
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| High | official school/government/court/publication sources | Strong evidence only when identity anchors also match |
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| Medium-high | LinkedIn, RocketReach, TheOrg, Tradeloop, ZoomInfo | Useful but needs corroboration |
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| Medium-low | Whitepages, 411, BeenVerified, NPD, FastBackgroundCheck | Lead only; mark unverified |
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| Low | obituaries/name-only pages | Usually weak/name-collision |
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| Reject | random blob/CDN/search-spam pages | Exclude from useful clusters |
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Do not let organization-only pages rank as likely person matches. An official SCAD page with no subject name is context, not identity evidence.
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## Matching pitfalls
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- Ignore one-letter middle initials for alias matching. A lone `m` from `Germaine M. Brown` matches almost every page.
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- Normalize phone numbers into all common forms: digits, dashed, dotted, `(xxx) xxx-xxxx`, `+1 xxx xxx xxxx`, `+1-xxx-xxx-xxxx`.
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- Separate likely target, possible target, weak/different, and rejected results.
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- Preserve source URL, query, provider, matched fields, score, and timestamp for every lead.
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- Treat Atlanta/Savannah/location-only matches as insufficient without identity anchors.
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## Compliance guardrails
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- OSINT results are leads, not verified facts.
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- Do not auto-contact from scraped or data-broker leads without human review.
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- Preserve source URL and timestamp for every claim.
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- Mark data-broker information as unverified until corroborated.
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## DRE integration path
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1. Add `Run OSINT` button on claim/debtor page.
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2. Call `person_search` with debtor anchors.
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3. Save JSON packet + markdown dossier to debtor record.
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4. Require human review before any collection action uses a lead.
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5. Later add paid providers only where MVP gaps are proven (People Data Labs, Trestle/Ekata-style phone intelligence, Pipl). |